1. Technical Field
The present invention relates to a technique for improving the quality of an image when print-outputting or display-outputting an inputted digital image of limited colors to, for example, a printer or a display.
2. Related Art
With the recent widespread distribution of electronic documents, it is generally requested to display or print digital images in high quality. For display or printing in high quality, an image quality improving technique is needed. Particularly, considerable attention is paid to an enlarging technique for outputting images in high quality to output devices of different resolutions. For example, in the case of outputting an image of 75 dpi in display resolution to a printer having a resolution of, say, 600 dpi, it is required to enlarge the image eight times as large as its original size. Of course, the enlarging process is applied also in the case of enlarging an image to a larger size.
Digital images can be classified according to the number of colors used throughout the whole of each image. For example, an image photographed with a digital camera contains a large number of colors and can be classified as a contone image. There is no clear definition of the contone image, but it can simply be considered to be an image in which 257 or more colors are used. For example, images which are outputted by a printer or a facsimile can be classified as binary images because there are used only two colors of black and white.
Further, as an image positioned intermediate between the contone image and the binary image there is a limited color image. Although there is no clear definition of the limited color image, either, it can simply be considered to be an image in which 255 or less colors are used throughout the entire image. In this sense, the binary image can be regarded as an image using only two colors out of limited color images and thus it can be said that the binary image corresponds to a special case of the limited color image.
Limited color images can be classified into images each prepared by reducing the number of colors of a contone image to 256 colors, e.g., a 256-color image obtained by reducing the number of colors of a natural image, and images each having 256 colors or less as an original number of colors, e.g., map, topographical map and GIS (geographical information system) information, CAD image and graphic image. As an exception, for example, an image resulting from gray conversion of a contone image of RGB and an image resulting from division of RGB are both images of 256 or less colors. Naturally, however, these images are regarded as contone images without including them in the category of limited color images.
Thus, a limited color image is expressed by only a small number of colors, e.g., 8, 16, or 256 colors, and these expressed colors can be associated with one another by, for example, a color map which is not obvious, and the image can be made into an image not subjected to an antialiasing process.
The antialiasing process is a technique for diminishing jaggy which appears at an edge portion of image. In the case of a limited color image, the antialiasing process is an image processing technique for multicolorizing an image to create a look of a smooth edge. Since the image is multicolored, the image having been subjected to the antialiasing process exhibits a stronger nature of a contone image than the limited color image.
By the antialiasing process, the edge portion becomes smooth in appearance and the image quality is improved, but the image quality can be improved also by enlarging the image to improve the resolution. FIG. 33 is explanatory diagram showing an example of an image quality improving process related to a conventional limited color image enlarging process. As noted above, the antialiasing process and the enlarging process for enlarging the resolution are known as image quality improving processes. Further, an antialiasing-enlarging process is also known as the combination process of the antialiasing process and the enlarging process as shown in FIG. 33. It can be said that the antialiasing-enlarging process is a process of a generic concept in comparison with each of the antialiasing process and the enlarging process. That is, if an image having been subjected to the antialiasing-enlarging process is again made into a limited color image, the image obtained is an enlarged image relative to the original image, and if a mean value contraction is applied to the original image size, there is obtained an antialiased image relative to the original image.
FIGS. 34A to 34H are explanatory diagrams showing an example of a relation between the image quality improving process and the concept of area occupancy. If an inherent edge line can be estimated as in FIG. 34B with respect to an original image shown in FIG. 34A, it is possible to obtain images of improved quality as in FIGS. 34C to 34F in terms of an area occupancy with the edge line crossing pixels. FIG. 34C is an antialiased image, FIG. 34D is an enlarged image, FIG. 34E is an antialiased-enlarged image, and FIG. 34F is a dot size modulated image. For the convenience of illustration, the difference of color is represented by different hatchings. Black and white portions need not always be black and white actually.
For example, with respect to a circled pixel in FIG. 34B, it is here assumed that the area occupancy of a black portion is 40% and that the color of the black portion is C1 and that of the white pixel is C2. Then, the value of the circled pixel can be obtained in terms of C1×0.4+C2×0.6. Also in the case of enlargement, the same calculation may be performed for pixels after the enlargement.
By thus processing each of pixels in the original image, for example by such a pixel-by-pixel processing as shown in FIG. 34G, the antialiased image shown in FIG. 34C is obtained. Moreover, for example as shown in FIG. 34H, if 2×2 pixels are produced from one pixel in the original image, there is obtained an antialiased-enlarged image as shown in FIG. 34E. If this antialiased-enlarged image is again made into a limited color image, there is obtained such an enlarged image as shown in FIG. 34D. If the antialiased-enlarged image shown in FIG. 34E is subjected to a mean value contraction, there is obtained such an antialiased image as shown in FIG. 34C. If the area occupancy of each pixel in the original image shown in FIG. 34B is replaced as it is by the size of pixel, there is obtained such a dot size modulated image as shown in FIG. 34F.
The above subject that an image is to be enlarged in high quality is a subject common to digital images. However, as noted above, generally-employed digital images are classified into several types and are different in properties, so for enlargement in high image quality it is necessary to adopt a method which takes the respective properties into account.